in Transportation Research Record: Journal of the Transportation Research Board (2016), 2565

In this study, the necessity for treating intrahousehold correlation was investigated by analyzing two travel behavior indexes, travel time and travel distance, for three important travel motivations ... [more ▼]

In this study, the necessity for treating intrahousehold correlation was investigated by analyzing two travel behavior indexes, travel time and travel distance, for three important travel motivations (commuting, shopping, and leisure). Data stemming from the 2010 Belgian National Household Travel Survey were used in the analysis. Two model approaches that accommodated intrahousehold correlation were compared, namely, the generalized linear mixed model (GLMM) and the generalized estimating equation (GEE) model. Both model approaches showed that high levels of intrahousehold correlation were present, and therefore the use of models that took into account intrahousehold correlation was strongly recommended. Results indicated that this requirement was the most urgent for noncommuting trips. Moreover, the results showed that the GLMM and the GEE model yielded comparable estimates in the case of normally distributed data. Furthermore, evidence was provided that the more the estimates of the intrahousehold correlation provided by the two approaches differed, the less the homogeneity of the parameters was ensured. In this regard, if one has to choose between the GLMM and the GEE model, the negative consequences of choosing an inappropriate covariance model in the case of GLMM especially favor the selection of the GEE model. Further research is needed to compare the two approaches in the context of nonnormally distributed travel behavior data. [less ▲]

in Proceedings of the 95th Annual Meeting of the Transportation Research Board (2016)

In this paper, the necessity for treating intra-household correlation is investigated by analyzing two travel behavior indices, i.e. travel time and travel distance, for three important travel motives ... [more ▼]

In this paper, the necessity for treating intra-household correlation is investigated by analyzing two travel behavior indices, i.e. travel time and travel distance, for three important travel motives (commuting, shopping, and leisure). Data stemming from the 2010 Belgian National Household Travel Survey are used in the analysis. Two model approaches that accommodate for intra-household correlation are compared, namely the generalized linear mixed model (GLMM) and GEE model approach. Both model approaches show that high levels of intra-household correlation are present, and therefore the use of models that take into account intra-household correlation, is strongly recommend. Results indicate that this requirement is the most urgent for non-commuting trips. Moreover, the results show that GLMM and GEE yield comparable estimates in the case of normally distributed data. Furthermore, evidence was provided that the more the estimates of the intra-household correlation provided by the two approaches differ, the less the homogeneity of the parameters is assured. In this regard, if one has to choose between the GLMM and GEE methodology, especially the negative consequences of choosing an inappropriate covariance model in the case of a GLMM model favor the selection of the GEE methodology. Further research is needed to compare the two approaches in the context of non-normally distributed travel behavior data. [less ▲]

The objective of this study is to examine the effect of road pricing on people’s tendency to adapt their current travel behavior. To this end, the relationship between changes in activity-travel behavior ... [more ▼]

The objective of this study is to examine the effect of road pricing on people’s tendency to adapt their current travel behavior. To this end, the relationship between changes in activity-travel behavior on the one hand and public acceptability and its most important determinants on the other are investigated by means of a stated adaptation experiment. Using a two-stage hierarchical model, it was found that behavioral changes themselves are not dependent on the perceived acceptability of road pricing itself, and that only a small amount of the variability in the behavioral changes were explained by socio-cognitive factors. The lesson for policy makers is that road pricing charges must surpass a minimum threshold in order to entice changes in activity-travel behavior and that the benefits of road pricing should be clearly communicated, taking into account the needs and abilities of different types of travelers. Secondly, earlier findings concerning the acceptability of push measures were validated, supporting transferability of results. In line with other studies, effectiveness, fairness and personal norm all had a significant direct impact on perceived acceptability. Finally, the relevance of using latent factors rather than aggregate indicators was underlined. [less ▲]

in Transportation Research Record: Journal of the Transportation Research Board (2010), 2183

To support policy makers combating travel-related externalities, quality data are required for the design and management of transportation systems and policies. To this end, much money has been spent on ... [more ▼]

To support policy makers combating travel-related externalities, quality data are required for the design and management of transportation systems and policies. To this end, much money has been spent on collecting household- and person-based data. The main objective of this paper is to assess the quality of origin-destination (O-D) matrices derived from household activity travel surveys. To this purpose, a Monte Carlo experiment is set up to estimate the precision of O-D matrices given different sampling rates. The Belgian 2001 census data, containing work- and school-related travel information for all 10,296,350 residents, are used for the experiment. For different sampling rates, 2,000 random stratified samples are drawn. For each sample, three O-D matrices are composed: one at the municipality level, one at the district level, and one at the provincial level. The correspondence between the samples and the population is assessed by using the mean absolute percentage error (MAPE) and a censored version of the MAPE (MCAPE). The results show that no accurate O-D matrices can be derived directly from these surveys. Only when half of the population is queried is an acceptable O-D matrix obtained at the provincial level. Therefore, use of additional information to grasp better the behavioral realism underlying destination choices and collection of information about particular O-D pairs by means of vehicle intercept surveys are recommended. In addition, results suggest using the MCAPE next to traditional criteria to examine dissimilarities between different O-D matrices. An important avenue for further research is the investigation of the effect of sampling proportions on travel demand model outcomes. [less ▲]

in Proceedings of the 89th Annual Meeting of the Transportation Research Board (DVD-ROM) (2010)

To support policy makers combating travel-related externalities, quality data is required for the design and management of transportation systems and policies. To this end, large amounts of money have ... [more ▼]

To support policy makers combating travel-related externalities, quality data is required for the design and management of transportation systems and policies. To this end, large amounts of money have been spent on collecting household and person-based data. The main objective of this paper is to assess the quality of origin-destination matrices derived from household activity/travel surveys. To this purpose, a Monte Carlo experiment is set up to estimate the precision of OD-matrices given different sampling rates. The Belgian 2001 census data, containing work/school-related travel information for all 10,296,350 residents, are used for the experiment. For different sampling rates, 2000 random stratified samples are drawn. For each sample, three origin-destination-matrices are composed: one at municipality level, one at district level, and one at provincial level. The correspondence between the samples and the population is assessed by using the Mean Absolute Percentage Error (MAPE) and a censored version of the MAPE (MCAPE). The results show that no accurate OD-matrices can be directly derived from these surveys. Only when half of the population is queried, an acceptable OD-matrix is obtained at provincial level. Therefore, it is recommended to use additional information to better grasp the behavioral realism underlying destination choices and to collect information about particular origin-destination pairs by means of vehicle intercept surveys. In addition, the results suggest using the MCAPE next to traditional criteria to examine dissimilarities between different OD matrices. An important avenue for further research is the investigation of the effect of sampling proportions on travel demand model outcomes. [less ▲]

in Proceedings of the 89th Annual Meeting of the Transportation Research Board (DVD-ROM) (2010)

The impact of public holidays on the underlying reasons of travel behavior, namely the activities people perform and the trips made, is seldom investigated. Therefore, in this paper the impact of public ... [more ▼]

The impact of public holidays on the underlying reasons of travel behavior, namely the activities people perform and the trips made, is seldom investigated. Therefore, in this paper the impact of public holidays on travel time expenditure in Flanders, differentiated by trip motive, is examined. The data used for the analysis stem from a household travel survey that was carried out in 2000. The main modeling approach that is employed is the zero-inflated Poisson regression approach, which explicitly takes into account the inherent contrast between travelers and non-travelers. The zero-inflated Poisson regression models yield findings that are harmonious with international literature: socio-demographic variables, temporal effects and transportation preferences contribute significantly in unraveling the variability of travel behavior. In particular it is shown that public holidays have a non-ignorable impact on daily travel behavior. Triangulation of both quantitative and qualitative techniques seems a solid roadway for further illumination of the underpinnings of travel behavior. [less ▲]

in Proceedings of the 89th Annual Meeting of the Transportation Research Board (DVD-ROM) (2010)

Many practitioners question the advantages of activity-based models over conventional four-step models in terms of replication of traffic counts. Therefore, in this paper, a framework is highlighted that ... [more ▼]

Many practitioners question the advantages of activity-based models over conventional four-step models in terms of replication of traffic counts. Therefore, in this paper, a framework is highlighted that actively links travel demand models in general, and activity-based models in particular, with traffic counts. Two approaches are presented that calibrate activity-based models with traffic counts, namely an indirect and a direct approach. The indirect approach tries to incorporate findings, based on the analysis of traffic counts, into the model components of the activity-based models. The direct approach calibrates the parameters of the travel demand model in such a way that the model replicates the observed traffic counts (quasi-)perfectly. A practical example is provided to illustrate the direct approach. The study area for this practical example is Hasselt, a Belgian city of about 70,000 residents, and its surrounding municipalities. The practical examples revealed that there is not a single roadway to success in calibrating activity based models, but that different options exist in fine-tuning the activity-based model. Notwithstanding, it is important to recognize some open issues and avenues for further research. First, it is not always appropriate to assume that traffic counts are completely correct. Setting up some belief-structure might increase the responsiveness of the activity-based model. In addition, the OD-matrix calibration that optimizes the correspondence between estimated and observed screen-line counts could negatively impact the correspondence to other measures such as vehicle miles traveled. To conclude, formulation of a multi-objective calibration method is a key challenge for further research. [less ▲]

in Proceedings of the 89th Annual Meeting of the Transportation Research Board (DVD-ROM) (2010)

Weather events can affect traffic in various ways; it can influence travel demand, traffic flows and traffic safety. This paper focuses on the impact of weather conditions on travel demand. The main ... [more ▼]

Weather events can affect traffic in various ways; it can influence travel demand, traffic flows and traffic safety. This paper focuses on the impact of weather conditions on travel demand. The main objectives of this paper are to test the hypothesis that the type of weather determines the likelihood of a change in travel behavior and to assay whether the changes in travel behavior due to weather conditions are dependent on the trip purpose. To this end, a stated adaptation study was conducted in Flanders (Dutch speaking region of Belgium). In total 586 respondents completed the survey, which was administered both on the Internet and via a traditional paper and-pencil questionnaire. To ensure an optimal correspondence between the survey sample composition and the Flemish population, the observations in the sample are weighted. To test the main hypotheses Pearson chi-square independence tests will be performed. Both the results from the descriptive analysis and the independence tests confirm that the type of weather matters, and that the changes in travel behavior in response to these weather conditions are highly dependent on the trip purpose. This dependence of behavioral adjustments on trip purposes provides policy makers with a deeper understanding of how weather conditions affect traffic. Further generalizations of the findings are possible by shifting the scope towards revealed travel behavior. Triangulation of both stated and revealed travel behavior on the one hand, and traffic intensities on the other hand, is certainly a key challenge for further research. [less ▲]

in Proceedings of the 12 World Conference on Transport Research (2010)

The overall final objective of this study is to investigate the effect of road pricing on people’s tendency to adapt their current travel behaviour. In order to reach this goal, a two-stage hierarchical ... [more ▼]

The overall final objective of this study is to investigate the effect of road pricing on people’s tendency to adapt their current travel behaviour. In order to reach this goal, a two-stage hierarchical model is estimated, concentrated around the concept of public acceptability. The research was conducted in Flanders, the Dutch-speaking region of Belgium, by means of an interactive stated adaptation survey, administered on the internet, involving 300 respondents. It is found that behavioural changes themselves are not dependent on the perceived acceptability of road pricing. In addition, earlier findings concerning the acceptability of push measures are validated, and the relevance of using latent factors rather than aggregate indicators is illustrated. [less ▲]

in Transportation Research Record: Journal of the Transportation Research Board (2010), 2175

Many practitioners question the advantages of activity-based models over conventional four-step models in regard to replication of traffic counts. This paper highlights a framework that actively links ... [more ▼]

Many practitioners question the advantages of activity-based models over conventional four-step models in regard to replication of traffic counts. This paper highlights a framework that actively links travel demand models in general and activity-based models in particular with traffic counts. Two approaches are presented that calibrate activity-based models with traffic count—an indirect and a direct approach. The indirect approach tries to incorporate findings based on the analysis of traffic counts into the components of the activity-based models. The direct approach calibrates the parameters of the travel demand model in such a way that the model replicates the observed traffic counts (quasi-) perfectly. A practical example is provided to illustrate the direct approach. The study area for this practical example is Hasselt, Belgium, a city of about 70,000 residents, and its surrounding municipalities. The practical examples revealed not a single roadway to success in calibrating activity-based models, but different options exist in fine-tuning the activity-based model. It is important to recognize some open issues and avenues for further research. First, it is not always appropriate to assume that traffic counts are completely correct. Setting up some belief structure might increase the responsiveness of the activity-based model. In addition, the origin-destination matrix calibration that optimizes the correspondence between estimated and observed screen-line counts could negatively affect the correspondence to other measures, such as vehicle miles traveled. To conclude, the formulation of a multiobjective calibration method is a key challenge for further research. [less ▲]

in Transportation Research Record: Journal of the Transportation Research Board (2010), 2157

Weather can influence travel demand, traffic flow, and traffic safety. A hypothesis—the type of weather determined the likelihood of a change in travel behavior, and changes in travel behavior because of ... [more ▼]

Weather can influence travel demand, traffic flow, and traffic safety. A hypothesis—the type of weather determined the likelihood of a change in travel behavior, and changes in travel behavior because of weather conditions depended on trip purpose—was assayed. A stated adaptation study was conducted in Flanders (the Dutch-speaking region of Belgium). A survey, completed by 586 respondents, was administered both on the Internet and as a traditional paper-and-pencil questionnaire. To ensure optimal correspondence between the survey sample composition and the Flemish population, observations in the sample were weighted. To test the main hypotheses, Pearson chi-square independence tests were performed. Results from both the descriptive analysis and the independence tests confirm that the type of weather matters and that changes in travel behavior in response to these weather conditions are highly dependent on trip purpose. This dependence of behavioral adjustments on trip purpose provides policy makers with a deeper understanding of how weather conditions affect traffic. Further generalizations of the findings are possible by shifting the scope toward revealed travel behavior. Triangulation of both stated and revealed travel behavior on the one hand and traffic intensities on the other hand is a key challenge for further research. [less ▲]

in Transportation Research Record: Journal of the Transportation Research Board (2010), 2157

The impact of public holidays on the underlying reasons for travel behavior, namely, the activities people perform and the trips made, is seldom investigated. Therefore, the effect of holidays on travel ... [more ▼]

The impact of public holidays on the underlying reasons for travel behavior, namely, the activities people perform and the trips made, is seldom investigated. Therefore, the effect of holidays on travel time expenditure in Flanders, differentiated by trip motive, is examined. The data used for the analysis stem from a household travel survey carried out in 2000. The zero-inflated Poisson regression approach is used; it explicitly takes into account the inherent contrast between travelers and nontravelers. The zero-inflated Poisson regression models yield findings that are harmonious with international literature: socio-demographic variables, temporal effects, and transportation preferences contribute significantly to unraveling the variability of travel behavior. In particular, it is shown that the effect of public holidays on daily travel behavior cannot be ignored. Triangulation of quantitative and qualitative techniques is a solid basis for insight into the underpinnings of travel behavior. [less ▲]

This paper focuses on the effect of weather conditions on daily traffic intensities (the number of cars passing a specific segment of a road). The main objective is to examination whether or not weather ... [more ▼]

This paper focuses on the effect of weather conditions on daily traffic intensities (the number of cars passing a specific segment of a road). The main objective is to examination whether or not weather conditions uniformly alter daily traffic intensities in Belgium, or in other words whether or not road usage on a particular location determines the size of the impacts of various weather conditions. This general examination is a contribution that allows policymakers to assess the appropriateness of countrywide versus local traffic management strategies. In addition, a secondary goal of this paper is to validate findings in international literature within a Belgian context. To achieve these goals, the paper analyzes the effects of weather conditions on both upstream (toward a specific location) and downstream (away from a specific location) traffic intensities at three traffic count locations typified by a different road usage. Perhaps the most interesting results of this study for policymakers are the heterogeneity of the weather effects between different traffic count locations, and the homogeneity of the weather effects on upstream and downstream traffic at specific locations. The results also indicate that snowfall, rainfall, and wind speed diminish traffic intensity, and high temperatures increase traffic intensity. Further generalizations of the findings might be possible by studying weather impacts on local roads and by shifting the focus of research toward travel behavior. [less ▲]

Time use surveys often are carried out to identify, classify and quantify social behaviour of people by focusing on the activities that people perform. Time use data, in the transportation field often ... [more ▼]

Time use surveys often are carried out to identify, classify and quantify social behaviour of people by focusing on the activities that people perform. Time use data, in the transportation field often referred to as activity-based data, can be used to study a variety of sociological, economic, and technological phenomena. Studying behaviour, social networks and transport patterns are a few of the topics that can be analysed based on these time use data. This first introductory paper discusses some emerging issues in the collection of travel-related data such as automatic spatial information recording using cell phones and GPS, and survey design experiences. On the one hand new technology offers the opportunity to record at a relative low cost a wide variety of the data, while on the other hand new problems occur. One of such problems for instance is the problems of ‘cold starts’ faced with GPS devices, clouding the first minutes of recording after each restart of the device after it was turned off completely. Notwithstanding, applications of new technologies offer the opportunity for performing detailed space-time analyses in different fields ranging from epidemiology to transportation science. Some of these applications are highlighted in this session. Next to the advantages and potential risks of new technologies, this introductory paper also discusses the combination of different modes to analyze space-time behaviour. In particular, this study investigates potential mixed mode design effects, observed in a large activity-based travel survey, using a PDA application on the one hand, and traditional paper and pencil diaries on the other hand. The mixed-mode effects are analysed using heteroscedastic linear regression models, taking into account not only mode-effects, but also potential fatigue-effects. The results show that in this mixed-mode survey no attrition effects are present, and that the survey mode (PDA versus paper and pencil) has no direct impact on the quantities investigated (number of out-of-home activities reported and number of trips). [less ▲]

in Proceedings of the 88th Annual Meeting of the Transportation Research Board (DVD-ROM) (2009)

An important policy instrument for governments to modify travel behavior and manage the increasing travel demand is the introduction of a congestion pricing system. In this study, the influence of a ... [more ▼]

An important policy instrument for governments to modify travel behavior and manage the increasing travel demand is the introduction of a congestion pricing system. In this study, the influence of a detailed classification of activities is examined to assess likely traveler response to congestion pricing scenarios. Despite the fact that most studies do not differentiate between activity categories, the value of time and in general the space-time properties and constraints of different types of activities vary widely. For this reason, it is of importance to provide sufficient detail and sensitivity in assessing the impact of congestion pricing scenarios. In addition, a first assessment of possible multi-faceted adaptation patterns of travelers is presented. For these purposes, a stated adaptation study was conducted in Flanders (Dutch speaking region of Belgium). The experiment was conducted through an interactive stated adaptation survey. In the stated adaptation experiment respondents could indicate their stated responses to the congestion pricing scenario. The most prevalent conclusion is that the activity type significantly predetermines the willingness to express a more environmental-friendly behavior (i.e. reducing the number of trips, reducing the total distance traveled, switching to more environmental-friendly modes). Also, the willingness to show ecological activity-travel behavior (e.g. carpooling and using public transport) in a non-pricing situation is a major differentiator of future behavior in a congestion pricing scenario. [less ▲]

in Proceedings of the 88th Annual Meeting of the Transportation Research Board (DVD-ROM) (2009)

Due to a variety of reasons, the previous century is characterized by an extraordinary growth in car use that has continued into the current century. This has resulted in serious environmental ... [more ▼]

Due to a variety of reasons, the previous century is characterized by an extraordinary growth in car use that has continued into the current century. This has resulted in serious environmental repercussions. Despite technological advancements, the externalities remain an ecological threat that can not be discarded by policy makers. Therefore, it is essential that policy makers focus on reducing car use and on stimulating the shift towards more environment-friendly transport modes. In this study, Q-methodology is adopted as the technique to segment people, and to ascertain which approaches and determinants matter to medium distance travel. Segmentation is important, as policy measures will be more efficient and effective if they are fine-tuned on specific target groups. The analysis revealed that four discourses preponderate the paradigm of environmentally sustainable transport: travelers who use public transport as a dominant alternative, car-dependent travelers, travelers with a positive perception of using public transport, and travelers with a preference for car use. Concerning rational, economic motives, individuals evaluate travel time reliability as most important. To increase the reliability policy makers should consider the use of separate bus lanes and traffic light manipulation. In addition, public transport can be made even more attractive, when costs of cars are made more variable by road or congestion charging. When the subjective motives are discussed, the differences between the different groups of travelers were more pronounced. Next to increasing the benefits of using public transport, policy makers should also pay attention to removing psycho-social barriers. [less ▲]

in Transportation Research Record: Journal of the Transportation Research Board (2009), 2136

In this paper, daily traffic counts are explained and forecast by different modeling philosophies: an approach using autoregressive integrated moving average (ARIMA) models with explanatory variables (i.e ... [more ▼]

In this paper, daily traffic counts are explained and forecast by different modeling philosophies: an approach using autoregressive integrated moving average (ARIMA) models with explanatory variables (i.e., the ARIMAX model) and approaches using a seasonal autoregressive integrated moving average (SARIMA) model as well as a SARIMA model with explanatory variables (i.e., the SARIMAX model). Special emphasis is placed on the investigation of seasonality in daily traffic data and on the identification and comparison of holiday effects at different sites. To get insight into prior cyclic patterns in the daily traffic counts, spectral analysis provides the required framework to highlight periodicities in the data. The analyses use data from single inductive loop detectors, which were collected in 2003, 2004, and 2005. Four traffic count locations are investigated in this study: an upstream and a downstream traffic count site on a highway used extensively by commuters, and an upstream and a downstream traffic count site on a highway typically used for leisure travel. The different modeling techniques show that weekly cycles appear to determine the variation in daily traffic counts. The comparison between seasonal and holiday effects at different site locations reveals that both the ARIMAX and the SARIMAX modeling approaches are valid frameworks for identifying and quantifying possible influencing effects. The techniques yield the insight that holidays have a noticeable impact on highways extensively used by commuters, while having a more ambiguous impact on highways typically used for leisure travel. Future research challenges are the modeling of daily traffic counts on secondary roads and the simultaneous modeling of underlying reasons for travel and revealed traffic patterns. [less ▲]

in Proceedings of the 88th Annual Meeting of the Transportation Research Board (DVD-ROM) (2009)

In this paper, daily traffic counts are explained and forecasted by different modeling philosophies, namely the ARIMAX and SARIMA(X) modeling approaches. Special emphasis is put on the investigation of ... [more ▼]

In this paper, daily traffic counts are explained and forecasted by different modeling philosophies, namely the ARIMAX and SARIMA(X) modeling approaches. Special emphasis is put on the investigation of the seasonality in the daily traffic data and on the identification and comparison of holiday effects at different site locations. To get prior insight in the cyclic patterns present in the daily traffic counts, spectral analysis provides the required framework to highlight periodicities in the data. Data originating from single inductive loop detectors, collected in 2003, 2004 and 2005, are used for the analyses. Four traffic count locations are investigated in this study, an upstream and downstream traffic count location on a highway that is excessively used by commuters and an upstream and downstream traffic count location on a highway that is typified by leisure traffic. The different modeling techniques pointed out that weekly cycles appear to determine the variation in daily traffic counts. The comparison between seasonal effects and holiday effects at different site locations revealed that both the ARIMAX and SARIMAX modeling approach are valid frameworks for the identification and quantification of possible influencing effects. The technique yielded the insight that holiday effects play a noticeable role on highways that are excessively used by commuters, while holiday effects have a more ambiguous effect on highways typified for their leisure traffic. Modeling of daily traffic counts on secondary roads, and simultaneous modeling of both the underlying reasons of travel and revealed traffic patterns, certainly are challenges for further research. [less ▲]

in Macharis, C.; Turcksin, L. (Eds.) Proceedings of the BIVEC-GIBET Transport Research Day 2009, Part II (2009)

Ever since car ownership and car use started to increase in Western Europe and the USA, transportation planners attempted to model people’s travel behavior. In the context of the Feathers project a ... [more ▼]

Ever since car ownership and car use started to increase in Western Europe and the USA, transportation planners attempted to model people’s travel behavior. In the context of the Feathers project a dynamic activity-based travel demand framework is developed for Flanders. In this paper, the complete survey design of the data collection effort required for such dynamic activity-based model is discussed. A mixed survey design of using a PDA application on the one hand, and using traditional paper and pencil diaries on the other hand, turns out to be a very suitable way of collecting detailed information about planned and executed activity-travel behavior of households. The results show that no attrition effects are present, not on the number of out-of-home activities reported, nor on the number of trips reported. Moreover the survey mode (PDA versus paper and pencil) has no direct impact on the quantities investigated. Notwithstanding, it is essential for further analysis on the Feathers data to explicitly take into account mode effects because of two reasons. First, the effect of explanatory variables can be influenced by the survey mode. Second, the variance in the estimation of the quantity investigated can differ significantly. Heteroscedatisc linear regression models provide the required framework to explicitly take into account these mode effects. [less ▲]